Predicting whether patients in an acute medical unit are physiologically fit-for-discharge using machine learning: A proof-of-concept-Reference-Cited by-同舟云学术

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Predicting whether patients in an acute medical unit are physiologically fit-for-discharge using machine learning: A proof-of-concept

Published:2024-11 Issue: Volume:191 Page:105586
ISSN:1386-5056
Container-title:International Journal of Medical Informatics
language:en
Short-container-title:International Journal of Medical Informatics

Author:

Garssen S.H.,Vernooij C.A.,Kant N.,Koning M.V.,Bosch F.H.,Doggen C.J.M.,Veldkamp B.P.,Verhaegh W.F.J.,Oude Wesselink S.F.

Publisher

Elsevier BV

Reference22 articles.

1. Effectiveness of acute medical units in hospitals: a systematic review;Scott;Int. J. Qual. Health Care,2009

2. D.N.H.b. Awang Husaini, J.F.S. Keasberry, K. Haji Abdul Mumin, H. Abdul Rahman, Causes of discharge delays from the acute medical unit (AMU) in a tertiary level teaching hospital, Brunei Darussalam. In: Proceedings of Singapore Healthcare. 2022;31:20101058211006143. doi: 10.1177/20101058211006143.

3. Impact and experiences of delayed discharge: a mixed-studies systematic review;Rojas-García;Health Expect.,2018

4. Hospital admission decision for patients with community-acquired pneumonia: variability among physicians in an emergency department;Dean;Ann. Emerg. Med.,2012

5. Reverse triage: more than just another method;Pollaris;Eur. J. Emerg. Med.,2016

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